{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "a28993b1-2612-474b-9aca-4a0cd99d3a0d",
   "metadata": {},
   "outputs": [],
   "source": [
    "#黑龙江全量用户分析\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "963f2355-4389-4fef-a880-7e4fc6c71fa9",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Ysten\\AppData\\Local\\Temp\\ipykernel_35916\\230654993.py:1: DtypeWarning: Columns (0) have mixed types. Specify dtype option on import or set low_memory=False.\n",
      "  df = pd.read_csv('C:/Users/Ysten/jupyter_doc/suixinkan/202407/all.csv', encoding='utf-8')\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>uid</th>\n",
       "      <th>short_prefer</th>\n",
       "      <th>long_prefer</th>\n",
       "      <th>vod_play_time</th>\n",
       "      <th>live_replay_play_time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>43212800</td>\n",
       "      <td>NaN</td>\n",
       "      <td>少儿:0.8906;电视剧:0.0900;电影:0.0194;纪录片:0.0000;资讯:0...</td>\n",
       "      <td>20.844420</td>\n",
       "      <td>10.070198</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2300103566172</td>\n",
       "      <td>NaN</td>\n",
       "      <td>教育:0.7000;电影:0.2701;电视剧:0.0234;综艺:0.0029;生活:0....</td>\n",
       "      <td>13.548500</td>\n",
       "      <td>109.714200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2301100720190</td>\n",
       "      <td>NaN</td>\n",
       "      <td>生活:0.9803;电影:0.0114;曲艺:0.0074;电视剧:0.0007;综艺:0....</td>\n",
       "      <td>17.063300</td>\n",
       "      <td>630.063600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2301100204634</td>\n",
       "      <td>NaN</td>\n",
       "      <td>电视剧:0.9166;电影:0.0834</td>\n",
       "      <td>0.047100</td>\n",
       "      <td>0.952500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>102140996</td>\n",
       "      <td>NaN</td>\n",
       "      <td>综艺:0.5377;电视剧:0.2107;少儿:0.1623;电影:0.0888;动漫:0....</td>\n",
       "      <td>2.301962</td>\n",
       "      <td>43.126434</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             uid short_prefer  \\\n",
       "0       43212800          NaN   \n",
       "1  2300103566172          NaN   \n",
       "2  2301100720190          NaN   \n",
       "3  2301100204634          NaN   \n",
       "4      102140996          NaN   \n",
       "\n",
       "                                         long_prefer  vod_play_time  \\\n",
       "0  少儿:0.8906;电视剧:0.0900;电影:0.0194;纪录片:0.0000;资讯:0...      20.844420   \n",
       "1  教育:0.7000;电影:0.2701;电视剧:0.0234;综艺:0.0029;生活:0....      13.548500   \n",
       "2  生活:0.9803;电影:0.0114;曲艺:0.0074;电视剧:0.0007;综艺:0....      17.063300   \n",
       "3                               电视剧:0.9166;电影:0.0834       0.047100   \n",
       "4  综艺:0.5377;电视剧:0.2107;少儿:0.1623;电影:0.0888;动漫:0....       2.301962   \n",
       "\n",
       "   live_replay_play_time  \n",
       "0              10.070198  \n",
       "1             109.714200  \n",
       "2             630.063600  \n",
       "3               0.952500  \n",
       "4              43.126434  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('C:/Users/Ysten/jupyter_doc/suixinkan/202407/all.csv', encoding='utf-8')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "d09cc231-bd0f-45b9-9634-c6914815aa0b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "总用户数：4724626\n",
      "短视频偏好为空的用户数：4407656, 占比 93.29\n",
      "长视频偏好为空的用户数：285513, 占比 6.04\n"
     ]
    }
   ],
   "source": [
    "print(\"总用户数：%s\" % df.shape[0])\n",
    "short_null = df['short_prefer'].isnull().sum()\n",
    "long_null = df['long_prefer'].isnull().sum()\n",
    "short_null_p = (short_null/df.shape[0]*100).round(2)\n",
    "long_null_p = (long_null/df.shape[0]*100).round(2)\n",
    "print(\"短视频偏好为空的用户数：%s, 占比 %s\" % (short_null, short_null_p))\n",
    "print(\"长视频偏好为空的用户数：%s, 占比 %s\" % (long_null, long_null_p))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "030182af-b80a-466f-a03d-9fbc44bad08c",
   "metadata": {},
   "outputs": [],
   "source": [
    "df =df.fillna(\"\")\n",
    "df['type'] = df.apply(lambda row: \n",
    "    '长短均无偏好' if row['short_prefer'] == \"\" and row['long_prefer'] == \"\" else\n",
    "    '有长偏好但无短偏好' if row['short_prefer'] == \"\" else\n",
    "    '有短偏好但无长偏好' if row['long_prefer'] == \"\" else\n",
    "    '长短均有偏好',\n",
    "    axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "5d8c11ad-4cf5-4f18-8b73-80c3e6477a49",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "type\n",
      "有短偏好但无长偏好        574\n",
      "有长偏好但无短偏好    4122717\n",
      "长短均无偏好        284939\n",
      "长短均有偏好        316396\n",
      "Name: count, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "value_counts = df['type'].value_counts().sort_index()\n",
    "print(value_counts)\n",
    "\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']\n",
    "plt.bar(value_counts.index, value_counts.values, color='b')\n",
    "plt.xlabel('类型')\n",
    "plt.ylabel('数量')\n",
    "plt.title('用户偏好存在情况分析')\n",
    "plt.tight_layout()  # 确保图形布局紧密\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "802ff71c-eba7-49d7-85a7-aa97c9fb4eea",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>uid</th>\n",
       "      <th>short_prefer</th>\n",
       "      <th>long_prefer</th>\n",
       "      <th>vod_play_time</th>\n",
       "      <th>live_replay_play_time</th>\n",
       "      <th>type</th>\n",
       "      <th>total</th>\n",
       "      <th>vod_percent</th>\n",
       "      <th>live_percent</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>43212800</td>\n",
       "      <td></td>\n",
       "      <td>少儿:0.8906;电视剧:0.0900;电影:0.0194;纪录片:0.0000;资讯:0...</td>\n",
       "      <td>20.844420</td>\n",
       "      <td>10.070198</td>\n",
       "      <td>偏重点播</td>\n",
       "      <td>30.914618</td>\n",
       "      <td>67.43</td>\n",
       "      <td>32.57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2300103566172</td>\n",
       "      <td></td>\n",
       "      <td>教育:0.7000;电影:0.2701;电视剧:0.0234;综艺:0.0029;生活:0....</td>\n",
       "      <td>13.548500</td>\n",
       "      <td>109.714200</td>\n",
       "      <td>直播爱好者</td>\n",
       "      <td>123.262700</td>\n",
       "      <td>10.99</td>\n",
       "      <td>89.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2301100720190</td>\n",
       "      <td></td>\n",
       "      <td>生活:0.9803;电影:0.0114;曲艺:0.0074;电视剧:0.0007;综艺:0....</td>\n",
       "      <td>17.063300</td>\n",
       "      <td>630.063600</td>\n",
       "      <td>直播爱好者</td>\n",
       "      <td>647.126900</td>\n",
       "      <td>2.64</td>\n",
       "      <td>97.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2301100204634</td>\n",
       "      <td></td>\n",
       "      <td>电视剧:0.9166;电影:0.0834</td>\n",
       "      <td>0.047100</td>\n",
       "      <td>0.952500</td>\n",
       "      <td>直播爱好者</td>\n",
       "      <td>0.999600</td>\n",
       "      <td>4.71</td>\n",
       "      <td>95.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>102140996</td>\n",
       "      <td></td>\n",
       "      <td>综艺:0.5377;电视剧:0.2107;少儿:0.1623;电影:0.0888;动漫:0....</td>\n",
       "      <td>2.301962</td>\n",
       "      <td>43.126434</td>\n",
       "      <td>直播爱好者</td>\n",
       "      <td>45.428396</td>\n",
       "      <td>5.07</td>\n",
       "      <td>94.93</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             uid short_prefer  \\\n",
       "0       43212800                \n",
       "1  2300103566172                \n",
       "2  2301100720190                \n",
       "3  2301100204634                \n",
       "4      102140996                \n",
       "\n",
       "                                         long_prefer  vod_play_time  \\\n",
       "0  少儿:0.8906;电视剧:0.0900;电影:0.0194;纪录片:0.0000;资讯:0...      20.844420   \n",
       "1  教育:0.7000;电影:0.2701;电视剧:0.0234;综艺:0.0029;生活:0....      13.548500   \n",
       "2  生活:0.9803;电影:0.0114;曲艺:0.0074;电视剧:0.0007;综艺:0....      17.063300   \n",
       "3                               电视剧:0.9166;电影:0.0834       0.047100   \n",
       "4  综艺:0.5377;电视剧:0.2107;少儿:0.1623;电影:0.0888;动漫:0....       2.301962   \n",
       "\n",
       "   live_replay_play_time   type       total  vod_percent  live_percent  \n",
       "0              10.070198   偏重点播   30.914618        67.43         32.57  \n",
       "1             109.714200  直播爱好者  123.262700        10.99         89.01  \n",
       "2             630.063600  直播爱好者  647.126900         2.64         97.36  \n",
       "3               0.952500  直播爱好者    0.999600         4.71         95.29  \n",
       "4              43.126434  直播爱好者   45.428396         5.07         94.93  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['total']=df['vod_play_time']+df['live_replay_play_time']\n",
    "df['vod_percent']=(df['vod_play_time']/df['total']*100).round(2)\n",
    "df['live_percent']=(df['live_replay_play_time']/df['total']*100).round(2)\n",
    "df['type'] = df['vod_percent'].apply(lambda x: \n",
    "    \"直播爱好者\" if 0 <= x < 20 else \n",
    "    \"偏重直播\" if 20 <= x < 40 else \n",
    "    \"均衡者\" if 40 <= x < 60 else \n",
    "    \"偏重点播\" if 60 <= x < 80 else \n",
    "    \"点播爱好者\")\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "f8811cc8-eed9-4fc4-b35f-3df87be8880c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "type\n",
      "偏重点播      514856\n",
      "偏重直播      505666\n",
      "均衡者       445801\n",
      "点播爱好者    1510984\n",
      "直播爱好者    1747319\n",
      "Name: count, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "value_counts = df['type'].value_counts().sort_index()\n",
    "print(value_counts)\n",
    "\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']\n",
    "plt.bar(value_counts.index, value_counts.values, color='b')\n",
    "plt.xlabel('类型')\n",
    "plt.ylabel('数量')\n",
    "plt.title('用户对直播点播偏好程度分析')\n",
    "plt.tight_layout()  # 确保图形布局紧密\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "61d2445e-6442-4984-9822-7fd947b2d949",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "直播爱好者中短视频偏好不为空的用户数：118802, 占比 6.8\n",
      "偏重直播中短视频偏好不为空的用户数：39091, 占比 7.73\n",
      "均衡者中短视频偏好不为空的用户数：33833, 占比 7.59\n",
      "偏重点播中短视频偏好不为空的用户数：36828, 占比 7.15\n",
      "点播爱好者中短视频偏好不为空的用户数：88416, 占比 5.85\n"
     ]
    }
   ],
   "source": [
    "df_1 = df[df['type'] == \"直播爱好者\"]\n",
    "short_null_1 = (df_1['short_prefer'] != \"\").sum()\n",
    "short_null_p_1 = (short_null_1/df_1.shape[0]*100).round(2)\n",
    "print(\"直播爱好者中短视频偏好不为空的用户数：%s, 占比 %s\" % (short_null_1, short_null_p_1))\n",
    "\n",
    "df_2 = df[df['type'] == \"偏重直播\"]\n",
    "short_null_2 = (df_2['short_prefer'] != \"\").sum()\n",
    "short_null_p_2 = (short_null_2/df_2.shape[0]*100).round(2)\n",
    "print(\"偏重直播中短视频偏好不为空的用户数：%s, 占比 %s\" % (short_null_2, short_null_p_2))\n",
    "\n",
    "df_3 = df[df['type'] == \"均衡者\"]\n",
    "short_null_3 = (df_3['short_prefer'] != \"\").sum()\n",
    "short_null_p_3 = (short_null_3/df_3.shape[0]*100).round(2)\n",
    "print(\"均衡者中短视频偏好不为空的用户数：%s, 占比 %s\" % (short_null_3, short_null_p_3))\n",
    "\n",
    "df_4 = df[df['type'] == \"偏重点播\"]\n",
    "short_null_4 = (df_4['short_prefer'] != \"\").sum()\n",
    "short_null_p_4 = (short_null_4/df_4.shape[0]*100).round(2)\n",
    "print(\"偏重点播中短视频偏好不为空的用户数：%s, 占比 %s\" % (short_null_4, short_null_p_4))\n",
    "\n",
    "df_5 = df[df['type'] == \"点播爱好者\"]\n",
    "short_null_5 = (df_5['short_prefer'] != \"\").sum()\n",
    "short_null_p_5 = (short_null_5/df_5.shape[0]*100).round(2)\n",
    "print(\"点播爱好者中短视频偏好不为空的用户数：%s, 占比 %s\" % (short_null_5, short_null_p_5))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "1fd25700-ddf6-432c-99d9-45aedb2c084a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "long_first\n",
      "          285513\n",
      "体育         80681\n",
      "健康           119\n",
      "儿童             1\n",
      "其他          8258\n",
      "动漫        199367\n",
      "央视名栏         606\n",
      "娱乐          2153\n",
      "少儿        622174\n",
      "巴西世界杯          3\n",
      "戏曲            83\n",
      "搞笑           111\n",
      "教育         11654\n",
      "新闻         47980\n",
      "旅游           139\n",
      "曲艺         14326\n",
      "栏目           785\n",
      "汽车2            8\n",
      "法治             6\n",
      "生活        141388\n",
      "电子竞技        4167\n",
      "电影        634013\n",
      "电视剧      2238403\n",
      "科教          1083\n",
      "纪录片        51180\n",
      "综艺        339285\n",
      "舞蹈            77\n",
      "诗歌            73\n",
      "财经          1329\n",
      "购物           160\n",
      "资讯         35752\n",
      "音乐          3749\n",
      "Name: count, dtype: int64\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['long_first'] = df['long_prefer'].str.split(';', expand=False).str[0].str.split(':', expand=False).str[0]\n",
    "first_type_counts = df['long_first'].value_counts().sort_index()\n",
    "print(first_type_counts)\n",
    "\n",
    "plt.figure(figsize=(15, 5))\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']\n",
    "plt.bar(first_type_counts.index, first_type_counts.values, color='b')\n",
    "plt.xlabel('大分类')\n",
    "plt.ylabel('数量')\n",
    "plt.title('用户对长视频一级分类的偏好分布')\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "cd53277d-ffdd-4653-96b2-bd92ddbf2551",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "long_first\n",
      "          285513\n",
      "体育         80681\n",
      "健康           119\n",
      "儿童             1\n",
      "其他          8258\n",
      "动漫        199367\n",
      "央视名栏         606\n",
      "娱乐          2153\n",
      "少儿        622174\n",
      "巴西世界杯          3\n",
      "戏曲            83\n",
      "搞笑           111\n",
      "教育         11654\n",
      "新闻         47980\n",
      "旅游           139\n",
      "曲艺         14326\n",
      "栏目           785\n",
      "汽车2            8\n",
      "法治             6\n",
      "生活        141388\n",
      "电子竞技        4167\n",
      "电影        634013\n",
      "电视剧      2238403\n",
      "科教          1083\n",
      "纪录片        51180\n",
      "综艺        339285\n",
      "舞蹈            77\n",
      "诗歌            73\n",
      "财经          1329\n",
      "购物           160\n",
      "资讯         35752\n",
      "音乐          3749\n",
      "Name: count, dtype: int64\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_short_null = df.dropna(subset=['short_prefer'])\n",
    "short_null_long_first_counts = df_short_null['long_first'].value_counts().sort_index()\n",
    "print(short_null_long_first_counts)\n",
    "\n",
    "plt.figure(figsize=(15, 5))\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']\n",
    "plt.bar(short_null_long_first_counts.index, short_null_long_first_counts.values, color='b')\n",
    "plt.xlabel('大分类')\n",
    "plt.ylabel('数量')\n",
    "plt.title('短视频偏好为空的用户对长视频一级分类的偏好分布')\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "200a858e-5cef-422e-9884-e6d9697153ad",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "最喜欢电视剧的用户短视频偏好不为空的人数为：140875, 占比 6.29\n",
      "最喜欢电影的用户短视频偏好不为空的人数为：52785, 占比 8.33\n",
      "最喜欢少儿的用户短视频偏好不为空的人数为：55240, 占比 8.88\n",
      "最喜欢综艺的用户短视频偏好不为空的人数为：18223, 占比 5.37\n",
      "最喜欢动漫的用户短视频偏好不为空的人数为：22175, 占比 11.12\n",
      "最喜欢资讯的用户短视频偏好不为空的人数为：589, 占比 1.65\n",
      "最喜欢新闻的用户短视频偏好不为空的人数为：304, 占比 0.63\n",
      "最喜欢生活的用户短视频偏好不为空的人数为：13455, 占比 9.52\n",
      "最喜欢体育的用户短视频偏好不为空的人数为：7832, 占比 9.71\n"
     ]
    }
   ],
   "source": [
    "df_first_1 = df[df['long_first'] == \"电视剧\"]\n",
    "short_first_null_1 = (df_first_1['short_prefer'] != \"\").sum()\n",
    "short_first_null_p_1 = (short_first_null_1/df_first_1.shape[0]*100).round(2)\n",
    "print(\"最喜欢电视剧的用户短视频偏好不为空的人数为：%s, 占比 %s\" % (short_first_null_1, short_first_null_p_1))\n",
    "\n",
    "df_first_2 = df[df['long_first'] == \"电影\"]\n",
    "short_first_null_2 = (df_first_2['short_prefer'] != \"\").sum()\n",
    "short_first_null_p_2 = (short_first_null_2/df_first_2.shape[0]*100).round(2)\n",
    "print(\"最喜欢电影的用户短视频偏好不为空的人数为：%s, 占比 %s\" % (short_first_null_2, short_first_null_p_2))\n",
    "\n",
    "df_first_3 = df[df['long_first'] == \"少儿\"]\n",
    "short_first_null_3 = (df_first_3['short_prefer'] != \"\").sum()\n",
    "short_first_null_p_3 = (short_first_null_3/df_first_3.shape[0]*100).round(2)\n",
    "print(\"最喜欢少儿的用户短视频偏好不为空的人数为：%s, 占比 %s\" % (short_first_null_3, short_first_null_p_3))\n",
    "\n",
    "df_first_4 = df[df['long_first'] == \"综艺\"]\n",
    "short_first_null_4 = (df_first_4['short_prefer'] != \"\").sum()\n",
    "short_first_null_p_4 = (short_first_null_4/df_first_4.shape[0]*100).round(2)\n",
    "print(\"最喜欢综艺的用户短视频偏好不为空的人数为：%s, 占比 %s\" % (short_first_null_4, short_first_null_p_4))\n",
    "\n",
    "df_first_5 = df[df['long_first'] == \"动漫\"]\n",
    "short_first_null_5 = (df_first_5['short_prefer'] != \"\").sum()\n",
    "short_first_null_p_5 = (short_first_null_5/df_first_5.shape[0]*100).round(2)\n",
    "print(\"最喜欢动漫的用户短视频偏好不为空的人数为：%s, 占比 %s\" % (short_first_null_5, short_first_null_p_5))\n",
    "\n",
    "df_first_6 = df[df['long_first'] == \"资讯\"]\n",
    "short_first_null_6 = (df_first_6['short_prefer'] != \"\").sum()\n",
    "short_first_null_p_6 = (short_first_null_6/df_first_6.shape[0]*100).round(2)\n",
    "print(\"最喜欢资讯的用户短视频偏好不为空的人数为：%s, 占比 %s\" % (short_first_null_6, short_first_null_p_6))\n",
    "\n",
    "df_first_7 = df[df['long_first'] == \"新闻\"]\n",
    "short_first_null_7 = (df_first_7['short_prefer'] != \"\").sum()\n",
    "short_first_null_p_7 = (short_first_null_7/df_first_7.shape[0]*100).round(2)\n",
    "print(\"最喜欢新闻的用户短视频偏好不为空的人数为：%s, 占比 %s\" % (short_first_null_7, short_first_null_p_7))\n",
    "\n",
    "df_first_8 = df[df['long_first'] == \"生活\"]\n",
    "short_first_null_8 = (df_first_8['short_prefer'] != \"\").sum()\n",
    "short_first_null_p_8 = (short_first_null_8/df_first_8.shape[0]*100).round(2)\n",
    "print(\"最喜欢生活的用户短视频偏好不为空的人数为：%s, 占比 %s\" % (short_first_null_8, short_first_null_p_8))\n",
    "\n",
    "df_first_9 = df[df['long_first'] == \"体育\"]\n",
    "short_first_null_9 = (df_first_9['short_prefer'] != \"\").sum()\n",
    "short_first_null_p_9 = (short_first_null_9/df_first_9.shape[0]*100).round(2)\n",
    "print(\"最喜欢体育的用户短视频偏好不为空的人数为：%s, 占比 %s\" % (short_first_null_9, short_first_null_p_9))"
   ]
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